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title: README |
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# OTAR3088 NLP-model collection |
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## Work Package 1 - Knowledge Extraction (NLP) |
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_**Background**_ |
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Within this working group of the greater _OTAR3088, 'Automating Knowledge Management'_ project, we aim to modernise and extend the current named entity recognition workflows of EuropePMC / Open Targets to cover an array of entity types of entities relevant to drug discovery (such as variants, biomarkers, tissues/cell types, adverse events, and assay conditions). These new entities will provide higher confidence in the relevance of a target-disease association. |
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Since NLP models are constantly updated and fine-tuned, we have created a modular, flexible framework that facilitates the creation of new NLP models. |
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_**OTAR3088 HuggingFace**_ |
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This organisation space details all of the data development and model generation of the project. Data is sectioned by the greater entity-type being studied by the group at a given time, sources of data are described in the data cards. Output models are also shared here. |
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_**Learn more about our project, resources and others:**_ |
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* [OTAR3088 - The project](https://home.opentargets.org/OTAR3088) |
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* [Our flexible NLP-model production pipeline](https://github.com/ML4LitS/OTAR3088) |
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* [Published Papers](https://www.tandfonline.com/doi/full/10.1080/17460441.2025.2490835) |
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